Evidence map›Paper›PMID 34869404›Full record

ReviewFrontiers in medicine2021

Psoriasis to Psoriatic Arthritis: The Application of Proteomics Technologies.

Fei Qi, Yaqi Tan, Amin Yao, Xutong Yang, Yanling He

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.7field-weighted citation impact, top 31% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 11 citations in OpenAlex.

  1. Anti-Psoriatic activity ofOpen veterinary journal · 2026
    Article
  2. Article
  3. Article
  4. Review
  5. Targeted Therapies in Psoriatic Arthritis-An Update.International journal of molecular sciences · 2023
    Review
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Fei QiDepartment of Dermatology, Capital Medical University Affiliated Beijing Chaoyang Hospital, Beijing, China.
Yaqi TanDepartment of Dermatology, Capital Medical University Affiliated Beijing Chaoyang Hospital, Beijing, China.
Amin YaoDepartment of Dermatology, Capital Medical University Affiliated Beijing Chaoyang Hospital, Beijing, China.
Xutong YangDepartment of Dermatology, Capital Medical University Affiliated Beijing Chaoyang Hospital, Beijing, China.
Yanling HeDepartment of Dermatology, Capital Medical University Affiliated Beijing Chaoyang Hospital, Beijing, China.
Beijing Chaoyang Emergency Medical Center · CNCapital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Psoriatic disease (PsD) is a spectrum of diseases that affect both skin [cutaneous psoriasis (PsC)] and musculoskeletal features [psoriatic arthritis (PsA)]. A considerable number of patients with PsC have asymptomatic synovio-entheseal inflammations, and approximately one-third of those eventually progress to PsA with an enigmatic mechanism. Published studies have shown that early interventions to the very early-stage PsA would effectively prevent substantial bone destructions or deformities, suggesting an unmet goal for exploring early PsA biomarkers. The emergence of proteomics technologies brings a complete view of all involved proteins in PsA transitions, offers a unique chance to map all potential peptides, and allows a direct head-to-head comparison of interaction pathways in PsC and PsA. This review summarized the latest development of proteomics technologies, highlighted its application in PsA biomarker discovery, and discussed the possible clinical detectable PsA risk factors in patients with PsC.

Indexed as

biomarkersproteomicspsoriasispsoriatic arthritispsoriatic disease

Identifiers

PMID34869404
PMCPMC8635007
OpenAlexW3211847913

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.